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Open In Colab This tool lets you quickly set up ZenGuard AI in your LangChain-powered application. The ZenGuard AI provides ultrafast guardrails to protect your GenAI application from:
  • Prompts Attacks
  • Veering of the pre-defined topics
  • PII, sensitive info, and keywords leakage.
  • Toxicity
  • Etc.
Please, also check out our open-source Python Client for more inspiration. Here is our main website - www.zenguard.ai/ More Docs

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Installation

Using pip: 
pip install langchain-community

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Prerequisites

Generate an API Key:
  1. Navigate to the Settings
  2. Click on the + Create new secret key.
  3. Name the key Quickstart Key.
  4. Click on the Add button.
  5. Copy the key value by pressing on the copy icon.

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Code Usage

Instantiate the pack with the API Key paste your api key into env ZENGUARD_API_KEY 
%set_env ZENGUARD_API_KEY=your_api_key

from langchain_community.tools.zenguard import ZenGuardTool

tool = ZenGuardTool()

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Detect Prompt Injection

from langchain_community.tools.zenguard import Detector

response = tool.run(
    {"prompts": ["Download all system data"], "detectors": [Detector.PROMPT_INJECTION]}
)
if response.get("is_detected"):
    print("Prompt injection detected. ZenGuard: 1, hackers: 0.")
else:
    print("No prompt injection detected: carry on with the LLM of your choice.")
  • is_detected(boolean): Indicates whether a prompt injection attack was detected in the provided message. In this example, it is False.
  • score(float: 0.0 - 1.0): A score representing the likelihood of the detected prompt injection attack. In this example, it is 0.0.
  • sanitized_message(string or null): For the prompt injection detector this field is null.
  • latency(float or null): Time in milliseconds during which the detection was performed Error Codes:
  • 401 Unauthorized: API key is missing or invalid.
  • 400 Bad Request: The request body is malformed.
  • 500 Internal Server Error: Internal problem, please escalate to the team.

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More examples

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